On Thu, Dec 20, 2018 at 12:18 PM Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:

Hi Martin

you can use whichever surface you want - they are just different
biological questions. The files we write out by default relate to the
white surface, but you can certainly generate the equivalent for the pial
using mris_curvature.

In general the curvature is 1/r, where r is the radius of an inscribed
circle that is tangent to the surface in that direction. So bigger
curvature implies smaller r (and sharper folds).

As for you question (2), I think that is a biological one and depends on
the effect you are looking for (unless I am misunderstanding)

cheers
Bruce

On
Thu, 20 Dec 2018, Martin Juneja wrote:

>
>         External Email - Use Caution
>
> Thank you so much every one for helping me in this regard. I have some follow up questions:
> I am interested in associating mean curvature (H) with some behavioral measure. After extracting
> subject-wise mean curvature estimates, I found a significant positive association between mean
> curvature and those behavioral measures. My questions are:
>
> (1). Why did Dr. Greve suggested to use white surface for estimating mean curvature, and not pial?
> What's the exact differences in both - is the only difference is that one is used for mean curvature
> from white matter (white surface) and the other from gray matter? I am not sure why one is
> recommended over the other?
> (2). If I want to use my own spherical ROIs for mean curvature estimation, how much radius is enough
> to draw spheres around peak coordinates?
> (3). Using white surface as recommended as Dr. Greve, I get (-) values for all the subjects, please
> see attached plot. Here mean curvature values are plotted along Y-axis. So here more negative values
> (.e.g ~ -0.07) represent sharper folds or less negative values (e.g. ~ -0.04) represent sharper
> folds? If I take absolute values of mean curvature, this association shown in attached plot changes
> from positive to negative. Can you please help me in interpreting the differences in more negative
> and less negative values here?
>
> Any additional information about this measure will also be very useful, as I am using this parameter
> for the first time.
>
> Thanks a lot.
>
> On Wed, Dec 19, 2018 at 4:24 PM Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:
> a 2D manifold has two principal curvatures, usually called k1 and k2,
> which are the curvature in the direction of maximum curvature and minimum
> curvature (they are also the eigenvalues and eigenvectors of the Hessian of
> the surface if it is expressed as a function over the tangent bundle). The
> Gaussian (K) and mean (H) curvatures are then:
>
> K = k1*k2
> H = (k1+k2)/2
>
> cheers
> Bruce
>
>
> On Wed, 19 Dec 2018, Greve, Douglas N.,Ph.D. wrote:
>
> > I'll leave that up to Bruce and Rudolph
> >
> > On 12/19/2018 05:37 PM, Martin Juneja wrote:
> >>
> >>         External Email - Use Caution
> >>
> >> Thanks Dr. Greve. That works, but both white.K and white.H are giving
> >> me very different output values.
> >>
> >> For example, for first few subjects I get:
> >> -0.00237 -0.00450 -0.00204 0.00113 -0.00228 -0.00958
> >> -0.00314 0.00180 -0.00452 if I use white.K
> >> -0.05809 -0.05799 -0.06457 -0.07254 -0.07208 -0.05023
> >> -0.06044 -0.09338 -0.09178 if I use white.H
> >>
> >> Can you please tell me the difference between white.K and white.H
> >> conceptually and mathematically?
> >>
> >> On Wed, Dec 19, 2018 at 2:27 PM Greve, Douglas N.,Ph.D.
> >> <DGREVE@mgh.harvard.edu <mailto:DGREVE@mgh.harvard.edu>> wrote:
> >>
> >> something like --meas white.K or white.H
> >>
> >>
> >> On 12/19/2018 04:23 PM, Martin Juneja wrote:
> >> >
> >> >         External Email - Use Caution
> >> >
> >> > Hi,
> >> >
> >> > Just like volume, I have "Folding Index" measures saved in
> >> > lh/rh.aparc.stats files for each subject.
> >> >
> >> > If I am using mris_preproc *--meas volume* --out CV/lh.CV.mgh
> >> command
> >> > to concat cortical volume files from all subjects, then how can
> >> I use
> >> > this command for "folding index" output file?
> >> >
> >> > Any help will be really appreciated.
> >> >
> >> >
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